D. Kim Rossmo PhD
School of Criminal Justice and Criminology, Texas State University
Lorie Velarde MSc
Irvine Police Department
Thomas Mahood MSc
Formerly with Riverside Mountain Rescue Unit
USA
Email krossmo@txstate.edu
http://dx.doi.org/10.61618/SIIV8474
Abstract
This article is a follow-up to a 2019 analysis that applied Bayesian probability techniques to the search
for a missing hiker in Joshua Tree National Park. In February 2022, that hiker was found. Here, we
compare the location of his remains with the results of our prediction model and discuss further
implications for optimizing wilderness search and rescue.
KEY WORDS: Wilderness Search and Rescue, Lost Persons, Bayesian Analysis, Resource
Optimization